POS1165 UNBIASED PROTEOMIC APPROACH TO IDENTIFY NOVEL BIOMARKERS OF DISEASE ACTIVITY IN ANCA-ASSOCIATED VASCULITIS
Authors: N. Atallah, V. Panossian, X. Fu, C. Cook, Z. Wallace
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> ANCA-associated vasculitis (AAV) carries excessive morbidity and mortality owing to the delay in diagnosis and limited prognostication. Identifying clinically useful biomarkers of disease activity that facilitate accurate prognostication would help personalize management decisions. Biomarkers used in day-to-day practice include PR3- or MPO-ANCA, CRP, and ESR, but these poorly predict future disease activity. Few studies have examined a limited number of circulating proteins as biomarkers, including BCA-1, MMP-3, TIMP-1<sup>[1-4]</sup>. We previously leveraged a high-throughput, unbiased approach to investigate 92 potential biomarkers for disease prognostication in AAV patients and identified 5 potential biomarkers. <h3>Objectives</h3> To further investigate the association of 5 novel protein biomarkers with AAV disease activity. <h3>Methods</h3> Serum samples from patients in the Mass General Brigham (MGB) AAV cohort were retrieved from the MGB Biobank following IRB approval. We chose a random 78 subjects who had AAV. We classified disease activity as "Active" or "Remission" at sample collection. The O-link high-throughput proteomic assay was used to measure the levels of 5 proteins of interest (MCP3, TNFSF-14, OSM, Flt3L, and SCF). For analysis, protein levels were first normalized. We compared protein levels in active disease vs remission. ESR, CRP, white blood cell (WBC) count and platelet levels were extracted for comparison. Using the mean value of each potential biomarker in the cohort as cut-off values, we determined the odds ratio (OR) and the area under the receiver operating curve (AUC) of the association of elevated biomarkers with active disease. <h3>Results</h3> Of n=78, the mean age was 57.3 +/- 17.6, 55% were female, and 28% had active disease at sample collection. When examining the outcome of active disease vs remission, abnormal levels of OSM, TNF-SF-14, Flt3L, and SCF differentiated disease states: OR of 5.10 (p=0.005), 3.71 (p=0.017), 0.13 (p=0.001), and 0.34 (p=0.040), respectively. AUC analysis indicated that TNF-SF-14 (0.731, CI 0.601-0.862), OSM (0.745, CI 0.622-0.867), and Flt3L (0.757, CI 0.644-0.871) were more strongly associated with active disease than other biomarkers, including WBC (0.703, CI 0.566-0.840), platelets (0.680, CI 0.551-0.809), CRP (0.549, CI 0.376-0.721), and ESR (0.547, CI 0.372-0.722). <h3>Conclusion</h3> Using a high-throughput, unbiased proteomics approach, we further investigated 5 novel candidate markers differentiating active AAV disease from remission. These proteins likely reflect different states of immune activation during active disease and outperform conventional inflammatory markers (e.g., CRP, ESR) as well as WBC and platelets. Our study has certain limitations, including sample size, a cross-sectional study design, and requires validation across diverse, longitudinal cohorts. The potential for biomarkers that accurately identify those individuals in remission compared to active disease may facilitate tailored, personalized therapeutic intervention, which avoids unnecessary exposure to the toxic side effects of immunomodulatory agents. <h3>References</h3> [1]Monach, et al. ACR Open Rheum 2022; 4:168. [2]Berti, et al. J Autoimmun 2019; 105:102302. [3]Monach, et al. Ann Rheum Dis 2013; 72:1342. [4]Monach, et al. Arthritis Rheum 2011; 63:3988. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.